IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i10p2917-d556922.html
   My bibliography  Save this article

Optimal Control Strategies for Switchable Transparent Insulation Systems Applied to Smart Windows for US Residential Buildings

Author

Listed:
  • Mohammad Dabbagh

    (Civil, Environmental, and Architectural Engineering Department, University of Colorado Boulder, Boulder, CO 80309, USA)

  • Moncef Krarti

    (Civil, Environmental, and Architectural Engineering Department, University of Colorado Boulder, Boulder, CO 80309, USA)

Abstract

This paper evaluates the potential energy use and peak demand savings associated with optimal controls of switchable transparent insulation systems (STIS) applied to smart windows for US residential buildings. The optimal controls are developed based on Genetic Algorithm (GA) to identify the automatic settings of the dynamic shades. First, switchable insulation systems and their operation mechanisms are briefly described when combined with smart windows. Then, the GA-based optimization approach is outlined to operate switchable insulation systems applied to windows for a prototypical US residential building. The optimized controls are implemented to reduce heating and cooling energy end-uses for a house located four US locations, during three representative days of swing, summer, and winter seasons. The performance of optimal controller is compared to that obtained using simplified rule-based control sets to operate the dynamic insulation systems. The analysis results indicate that optimized controls of STISs can save up to 81.8% in daily thermal loads compared to the simplified rule-set especially when dwellings are located in hot climates such as that of Phoenix, AZ. Moreover, optimally controlled STISs can reduce electrical peak demand by up to 49.8% compared to the simplified rule-set, indicating significant energy efficiency and demand response potentials of the SIS technology when applied to US residential buildings.

Suggested Citation

  • Mohammad Dabbagh & Moncef Krarti, 2021. "Optimal Control Strategies for Switchable Transparent Insulation Systems Applied to Smart Windows for US Residential Buildings," Energies, MDPI, vol. 14(10), pages 1-24, May.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:10:p:2917-:d:556922
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/10/2917/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/10/2917/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Evins, Ralph, 2013. "A review of computational optimisation methods applied to sustainable building design," Renewable and Sustainable Energy Reviews, Elsevier, vol. 22(C), pages 230-245.
    2. Tian, Wei, 2013. "A review of sensitivity analysis methods in building energy analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 20(C), pages 411-419.
    3. Casini, Marco, 2018. "Active dynamic windows for buildings: A review," Renewable Energy, Elsevier, vol. 119(C), pages 923-934.
    4. Reynolds, Jonathan & Rezgui, Yacine & Kwan, Alan & Piriou, Solène, 2018. "A zone-level, building energy optimisation combining an artificial neural network, a genetic algorithm, and model predictive control," Energy, Elsevier, vol. 151(C), pages 729-739.
    5. DeForest, Nicholas & Shehabi, Arman & Selkowitz, Stephen & Milliron, Delia J., 2017. "A comparative energy analysis of three electrochromic glazing technologies in commercial and residential buildings," Applied Energy, Elsevier, vol. 192(C), pages 95-109.
    6. Nundy, Srijita & Ghosh, Aritra, 2020. "Thermal and visual comfort analysis of adaptive vacuum integrated switchable suspended particle device window for temperate climate," Renewable Energy, Elsevier, vol. 156(C), pages 1361-1372.
    7. Jae-Hyang Kim & Jongin Hong & Seung-Hoon Han, 2021. "Optimized Physical Properties of Electrochromic Smart Windows to Reduce Cooling and Heating Loads of Office Buildings," Sustainability, MDPI, vol. 13(4), pages 1-30, February.
    8. Nguyen, Anh-Tuan & Reiter, Sigrid & Rigo, Philippe, 2014. "A review on simulation-based optimization methods applied to building performance analysis," Applied Energy, Elsevier, vol. 113(C), pages 1043-1058.
    9. Cho, Sung-Hwan & Shin, Kee-Shik & Zaheer-Uddin, M., 1995. "The effect of slat angle of windows with venetian blinds on heating and cooling loads of buildings in South Korea," Energy, Elsevier, vol. 20(12), pages 1225-1236.
    10. Ghosh, Aritra & Norton, Brian, 2019. "Optimization of PV powered SPD switchable glazing to minimise probability of loss of power supply," Renewable Energy, Elsevier, vol. 131(C), pages 993-1001.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Østergård, Torben & Jensen, Rasmus Lund & Maagaard, Steffen Enersen, 2018. "A comparison of six metamodeling techniques applied to building performance simulations," Applied Energy, Elsevier, vol. 211(C), pages 89-103.
    2. Nayara R. M. Sakiyama & Joyce C. Carlo & Leonardo Mazzaferro & Harald Garrecht, 2021. "Building Optimization through a Parametric Design Platform: Using Sensitivity Analysis to Improve a Radial-Based Algorithm Performance," Sustainability, MDPI, vol. 13(10), pages 1-25, May.
    3. Eleftheria Touloupaki & Theodoros Theodosiou, 2017. "Performance Simulation Integrated in Parametric 3D Modeling as a Method for Early Stage Design Optimization—A Review," Energies, MDPI, vol. 10(5), pages 1-18, May.
    4. Abdo Abdullah Ahmed Gassar & Choongwan Koo & Tae Wan Kim & Seung Hyun Cha, 2021. "Performance Optimization Studies on Heating, Cooling and Lighting Energy Systems of Buildings during the Design Stage: A Review," Sustainability, MDPI, vol. 13(17), pages 1-47, September.
    5. Ramos Ruiz, Germán & Fernández Bandera, Carlos & Gómez-Acebo Temes, Tomás & Sánchez-Ostiz Gutierrez, Ana, 2016. "Genetic algorithm for building envelope calibration," Applied Energy, Elsevier, vol. 168(C), pages 691-705.
    6. Yue, Naihua & Caini, Mauro & Li, Lingling & Zhao, Yang & Li, Yu, 2023. "A comparison of six metamodeling techniques applied to multi building performance vectors prediction on gymnasiums under multiple climate conditions," Applied Energy, Elsevier, vol. 332(C).
    7. García Kerdan, Iván & Raslan, Rokia & Ruyssevelt, Paul, 2016. "An exergy-based multi-objective optimisation model for energy retrofit strategies in non-domestic buildings," Energy, Elsevier, vol. 117(P2), pages 506-522.
    8. Ascione, Fabrizio & Bianco, Nicola & De Stasio, Claudio & Mauro, Gerardo Maria & Vanoli, Giuseppe Peter, 2016. "Multi-stage and multi-objective optimization for energy retrofitting a developed hospital reference building: A new approach to assess cost-optimality," Applied Energy, Elsevier, vol. 174(C), pages 37-68.
    9. Østergård, Torben & Jensen, Rasmus L. & Maagaard, Steffen E., 2016. "Building simulations supporting decision making in early design – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 187-201.
    10. Benedek Kiss & Jose Dinis Silvestre & Rita Andrade Santos & Zsuzsa Szalay, 2021. "Environmental and Economic Optimisation of Buildings in Portugal and Hungary," Sustainability, MDPI, vol. 13(24), pages 1-19, December.
    11. Guariso, Giorgio & Sangiorgio, Matteo, 2019. "Multi-objective planning of building stock renovation," Energy Policy, Elsevier, vol. 130(C), pages 101-110.
    12. Waibel, Christoph & Evins, Ralph & Carmeliet, Jan, 2019. "Co-simulation and optimization of building geometry and multi-energy systems: Interdependencies in energy supply, energy demand and solar potentials," Applied Energy, Elsevier, vol. 242(C), pages 1661-1682.
    13. Tian, Wei & Song, Jitian & Li, Zhanyong & de Wilde, Pieter, 2014. "Bootstrap techniques for sensitivity analysis and model selection in building thermal performance analysis," Applied Energy, Elsevier, vol. 135(C), pages 320-328.
    14. Shaik, Saboor & Maduru, Venkata Ramana & Kirankumar, Gorantla & Arıcı, Müslüm & Ghosh, Aritra & Kontoleon, Karolos J. & Afzal, Asif, 2022. "Space-age energy saving, carbon emission mitigation and color rendering perspective of architectural antique stained glass windows," Energy, Elsevier, vol. 259(C).
    15. Michalis Michael & Fabio Favoino & Qian Jin & Alessandra Luna-Navarro & Mauro Overend, 2023. "A Systematic Review and Classification of Glazing Technologies for Building Façades," Energies, MDPI, vol. 16(14), pages 1-47, July.
    16. García Kerdan, Iván & Raslan, Rokia & Ruyssevelt, Paul & Morillón Gálvez, David, 2017. "A comparison of an energy/economic-based against an exergoeconomic-based multi-objective optimisation for low carbon building energy design," Energy, Elsevier, vol. 128(C), pages 244-263.
    17. Cristina Brunelli & Francesco Castellani & Alberto Garinei & Lorenzo Biondi & Marcello Marconi, 2016. "A Procedure to Perform Multi-Objective Optimization for Sustainable Design of Buildings," Energies, MDPI, vol. 9(11), pages 1-15, November.
    18. Krarti, Moncef, 2023. "Optimal optical properties for smart glazed windows applied to residential buildings," Energy, Elsevier, vol. 278(PB).
    19. Alaia Sola & Cristina Corchero & Jaume Salom & Manel Sanmarti, 2018. "Simulation Tools to Build Urban-Scale Energy Models: A Review," Energies, MDPI, vol. 11(12), pages 1-24, November.
    20. Forde, Joe & Hopfe, Christina J. & McLeod, Robert S. & Evins, Ralph, 2020. "Temporal optimization for affordable and resilient Passivhaus dwellings in the social housing sector," Applied Energy, Elsevier, vol. 261(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:14:y:2021:i:10:p:2917-:d:556922. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.